pp_check.brmsfit {brms} | R Documentation |
Posterior Predictive Checks for brmsfit
Objects
Description
Perform posterior predictive checks with the help of the bayesplot package.
Usage
## S3 method for class 'brmsfit'
pp_check(
object,
type,
ndraws = NULL,
prefix = c("ppc", "ppd"),
group = NULL,
x = NULL,
newdata = NULL,
resp = NULL,
draw_ids = NULL,
nsamples = NULL,
subset = NULL,
...
)
Arguments
object |
An object of class |
type |
Type of the ppc plot as given by a character string.
See |
ndraws |
Positive integer indicating how many
posterior draws should be used.
If |
prefix |
The prefix of the bayesplot function to be applied. Either '"ppc"' (posterior predictive check; the default) or '"ppd"' (posterior predictive distribution), the latter being the same as the former except that the observed data is not shown for '"ppd"'. |
group |
Optional name of a factor variable in the model
by which to stratify the ppc plot. This argument is required for
ppc |
x |
Optional name of a variable in the model.
Only used for ppc types having an |
newdata |
An optional data.frame for which to evaluate predictions. If
|
resp |
Optional names of response variables. If specified, predictions are performed only for the specified response variables. |
draw_ids |
An integer vector specifying the posterior draws to be used.
If |
nsamples |
Deprecated alias of |
subset |
Deprecated alias of |
... |
Further arguments passed to |
Details
For a detailed explanation of each of the ppc functions,
see the PPC
documentation of the bayesplot
package.
Value
A ggplot object that can be further customized using the ggplot2 package.
Examples
## Not run:
fit <- brm(count ~ zAge + zBase * Trt
+ (1|patient) + (1|obs),
data = epilepsy, family = poisson())
pp_check(fit) # shows dens_overlay plot by default
pp_check(fit, type = "error_hist", ndraws = 11)
pp_check(fit, type = "scatter_avg", ndraws = 100)
pp_check(fit, type = "stat_2d")
pp_check(fit, type = "rootogram")
pp_check(fit, type = "loo_pit")
## get an overview of all valid types
pp_check(fit, type = "xyz")
## get a plot without the observed data
pp_check(fit, prefix = "ppd")
## End(Not run)